Trypano-PPI: A Web Server for Prediction of Unique Targets in Trypanosome Proteome by using Electrostatic Parameters of Protein-protein Interactions Yamilet Rodriguez-Soca, † Cristian R. Munteanu, ‡ Julia ´n Dorado, ‡ Alejandro Pazos, ‡ Francisco J. Prado-Prado, † and Humberto Gonza ´lez-Dı ´az* ,† Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain, and Department of Information and Communication Technologies, Computer Science Faculty, University of A Corun ˜ a, Campus de Elvin ˜a, 15071, A Corun ˜ a, Spain Received September 15, 2009 Abstract: Trypanosoma brucei causes African trypano- somiasis in humans (HAT or African sleeping sickness) and Nagana in cattle. The disease threatens over 60 million people and uncounted numbers of cattle in 36 countries of sub-Saharan Africa and has a devastating impact on human health and the economy. On the other hand, Trypanosoma cruzi is responsible in South America for Chagas disease, which can cause acute illness and death, especially in young children. In this context, the discovery of novel drug targets in Trypanosome proteome is a major focus for the scientific community. Recently, many researchers have spent important efforts on the study of protein-protein interactions (PPIs) in pathogen Trypanosome species concluding that the low sequence identities between some parasite proteins and their hu- man host render these PPIs as highly promising drug targets. To the best of our knowledge, there are no general models to predict Unique PPIs in Trypanosome (TPPIs). On the other hand, the 3D structure of an increasing number of Trypanosome proteins is reported in databases. In this regard, the introduction of a new model to predict TPPIs from the 3D structure of proteins involved in PPI is very important. For this purpose, we introduced new protein-protein complex invariants based on the Markov average electrostatic potential  k (R i ) for amino acids located in different regions (R i ) of i-th protein and placed at a distance k one from each other. We calculated more than 30 different types of parameters for 7866 pairs of proteins (1023 TPPIs and 6823 non-TPPIs) from more than 20 organisms, including parasites and human or cattle hosts. We found a very simple linear model that predicts above 90% of TPPIs and non-TPPIs both in training and independent test subsets using only two parameters. The parameters were d  k (s) ) | k (s 1 ) -  k (s 2 )|, the absolute difference between the  k (s i ) values on the surface of the two proteins of the pairs. We also tested nonlinear ANN models for comparison purposes but the linear model gives the best results. We imple- mented this predictor in the web server named Trypan- oPPI freely available to public at http://miaja.tic.udc.es/ Bio-AIMS/TrypanoPPI.php. This is the first model that predicts how unique a protein-protein complex in Try- panosome proteome is with respect to other parasites and hosts, opening new opportunities for antitrypanosome drug target discovery. Keywords: Trypanosoma proteome • African trypanoso- miasis • Chagas disease • Markov chains • protein-protein interactions • 3D-electrostatic potential • protein surface • machine learning • artificial neural networks Introduction African trypanosomiasis is a vector-borne parasitic disease caused by protozoan parasites of the Trypanosoma genus. Trypanosoma brucei species can infect both humans and animals, causing Human African Trypanosomiasis (HAT, also known as African sleeping sickness) in man and Nagana in cattle. The disease threatens over 60 million people and uncounted numbers of cattle in 36 countries of sub-Saharan Africa and has a devastating impact on human health and the economy in affected areas. Unless treated, HAT is always fatal. Political instability and economic problems are leading factors for the reduced efficacy in vector and disease control, resulting in a resurgence of disease that continues to this day (http:// www.who.int/tdr). On the other hand, Trypanosoma cruzi is responsible in South America for Chagas disease, which can cause acute illness and death, especially in young children. More commonly, patients develop a chronic form of the disease that affects most organs of the body, often causing fatal damage to the heart and digestive tract. Transmission occurs via bloodsucking triatomine bugs and congenitally from mother to the unborn child but can also occur through contaminated blood transfusions (http://www.who.int/en/). 1 Control of HAT relies primarily on chemotherapy. Nevertheless, there is a very limited arsenal of drugs, but they generally have shortcomings, such as high toxicity and emerging resistance. The drugs currently available to treat HAT have been available for more than half a century. Early stages of HAT are treated with * To whom correspondence should be addressed. H. Gonza ´lez-Dı ´az: Faculty of Pharmacy, USC, Spain. Phone: +34-981-563100. Fax: +34-981 594912. E-mail: humberto.gonzalez@usc.es or gonzalezdiazh@yahoo.es. † University of Santiago de Compostela. ‡ University of A Corun ˜a. 1182 Journal of Proteome Research 2010, 9, 1182–1190 10.1021/pr900827b  2010 American Chemical Society Published on Web 11/30/2009